Zequn Jie
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 2%
- Biomedical Engineering
- Aerospace Engineering top 10%
- Media Technology top 5%
- Topics
- Advanced Neural Network Applications (21 papers)Advanced Image and Video Retrieval Techniques (20 papers)Multimodal Machine Learning Applications (15 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Image ProcessingPattern Recognition
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Zequn Jie
46 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 116
- Computer Vision and Pattern Recognition 1.6k
- Artificial Intelligence 563
- Biomedical Engineering 132
- Aerospace Engineering 107
- Media Technology 100
Countries citing papers authored by Zequn Jie
This map shows the geographic impact of Zequn Jie's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Zequn Jie with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zequn Jie more than expected).
Fields of papers citing papers by Zequn Jie
This network shows the impact of papers produced by Zequn Jie. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Zequn Jie. The network helps show where Zequn Jie may publish in the future.
Co-authorship network of co-authors of Zequn Jie
This figure shows the co-authorship network connecting the top 25 collaborators of Zequn Jie. A scholar is included among the top collaborators of Zequn Jie based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Zequn Jie. Zequn Jie is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 10 | |
| 3 | 6 | |
| 4 | 3 | |
| 5 | 10 | |
| 6 | 14 | |
| 7 | 8 | |
| 8 | 5 | |
| 9 | 17 | |
| 10 | 42 | |
| 11 | 126 | |
| 12 | 17 | |
| 13 | 23 | |
| 14 | Central Similarity Hashing via Hadamard matrix. | 2 |
| 15 | Learning Object-Wise Semantic Representation for Detection in Remote Sensing Imagery | 18 |
| 16 | A Sufficient Condition for Convergences of Adam and RMSPropbreakdown → | 264 |
| 17 | Policy Optimization with Demonstrations | 37 |
| 18 | 197 | |
| 19 | Predicting Scene Parsing and Motion Dynamics in the Future | 18 |
| 20 | Multi-Path Feedback Recurrent Neural Network for Scene Parsing | 10 |
About Zequn Jie
Zequn Jie is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Media Technology, having authored 47 papers that have together received 2.0k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (21 papers), Advanced Image and Video Retrieval Techniques (20 papers) and Multimodal Machine Learning Applications (15 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), Artificial Intelligence (563 citations) and Media Technology (100 citations). Zequn Jie has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Jiashi Feng, Wei Liu, Lin Ma, Shuicheng Yan, Li Shen, Fangyu Zou, Weizhong Zhang, Jingyuan Chen, Osamu Yoshie and Tat‐Seng Chua. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.